The current project investigates the role of protein intrinsic disorder (ID) in mediating signaling in the transcription factor family of proteins, a process known as allostery. By measuring the stability and DNA binding affinity for a number of naturally occurring variants of the glucocorticoid receptor (GR) transcription factor and comparing these values to the transcriptional activity in cells, this project provides a framework for understanding allosteric signaling in proteins containing ID. The resulting experimental data will be used to construct a quantitative, predictive model of allostery. The intellectual merits of the proposed activities are two-fold. First these studies provide the first systematic analysis of ID-mediated allostery using both biophysical studies and live cell assays of function. Second, these studies challenge a recently developed ensemble allosteric model designed to quantitatively characterize allostery in terms of the intrinsic stabilities of cooperative elements of structure and the interaction energies between them. As such, this research represents an advance over previous qualitative and largely speculative models for ID function, and provides one of the first quantitative descriptions of how and why proteins use intrinsic disorder.
The broader impacts of the project are two-fold, and focus on research, education and the bridge between these two activities. First, the primary goal of the research is to experimentally determine the allosteric control present in GR. However, GR shares architecture with the estrogen (ER), progesterone (PR), androgen (AR), and vitamin D (VDR) receptors, all of which play a vital role in hormone-dependent cell signaling and regulation. As such, insights gained from the current research will directly impact understanding in these other systems. Second, a key objective of the research is to derive a quantitative model that is subject to simulation and validation. As part of two previous NSF proposals, the Principal Investigator has developed a significant amount of computer-based course work focuses on modeling of dynamic biological systems. The models developed as part of the current research will be directly integrated into the graduate and undergraduate curriculum at Johns Hopkins University, and thus will not only play a vital role in the education of biology students, it will significantly expand the biology students? access to computational methods and technologies.
